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The Japan Meteorological Agency defines extreme climate events as phenomena occurring once every 30 years or less. To prepare for disasters, we investigated future projections of 30-year return values of heavy precipitation in the Tohoku District of northern Japan based on a large number of ensemble warming projections that are dynamically downscaled to 5-km grids under the Social Implementation Program on Climate Change Adaptation Technology. The 30-year return values of daily and hourly precipitation are projected to significantly increase under global warming, indicating the strengthening of extremely heavy rainfall. Their averaged ratios across the Tohoku District in the 2-K and 4-K warmer climates to those in the present climate are 1.12 and 1.30 times for daily precipitation and 1.18 and 1.45 times for hourly precipitation, respectively. In particular, the 30-year return values are enormous on the eastern slopes of the Kitakami and Abukuma Mountains and the Ou Mountain Range. The rates of increase in the 30-year return values are pronounced in the northern part of Tohoku, where the surface air temperature increase is more significant than in other regions. These results suggest the need to upgrade disaster prevention measures for heavy rainfall as a climate change adaptation in the Tohoku District. We also examined the regional dependency of seasonal variation in the occurrence rates of daily and hourly extreme events. The results indicated that the occurrence rates tend to be relatively high on the Sea of Japan side of the Tohoku District in July due to the Baiu front, over the entire Tohoku District in August due to strong convective instability, and on the Pacific Ocean side due to September typhoons and autumn stationary fronts. This seasonality is projected to remain almost unchanged under warmer conditions. [ABSTRACT FROM AUTHOR]

It is important to understand the mechanisms of heavy rainfall events, as such information could improve forecasting of these events and help mitigate their adverse impacts on life and property. In this study, we analyzed hourly stable isotopic compositions in water vapor (δ18Ov and d‐excessv) during heavy rainfall events in the summer monsoon season (June to September) from 2013 to 2023 in Nanjing, eastern China. These data were extracted from the longest data set of high‐resolution and continuous in situ observations of water vapor isotopes globally. Based on these data, we identified four evolution patterns of δ18Ov during heavy rainfall events, corresponding to different weather systems: slow‐declining (tropical cyclone interacting with mid‐ and high‐latitude system), W‐shaped (tropical cyclone), U‐shaped (cold vortex system), and inclined L‐shaped (upper‐level trough system). The isotopic variations suggest that heavy rainfall events in eastern China were mainly sustained by moisture from adjacent oceans (including the South China Sea and the East China Sea) and terrestrial environment rather than from the distant Indian Ocean as previously suggested. In addition, for some heavy rainfall events with an intermittent period, the nearby oceanic moisture transport alters before and after the intermittent period due to an intensity change or overall transition of low‐level weather systems. This study serves as a benchmark for tracing heavy rainfall processes in East Asia using high‐resolution water vapor isotopes. Plain Language Summary: Flooding is a major source of mortality and damage in heavy rainfall events. Accurate forecasting of heavy rainfall remains a significant challenge due to inadequate understanding of the complex moisture sources and transport processes. Stable isotopes in atmospheric water vapor could provide crucial information on how water is transported and mixed in the atmosphere. The 11‐year in situ online observations of water vapor isotopes indicated that heavy rainfall events in eastern China were mainly sustained by moisture from adjacent oceans and terrestrial environment rather than from the distant Indian Ocean as previously suggested. Our results provide a valuable high‐resolution data set of water vapor isotopes for heavy rainfall events and a benchmark for tracing heavy rainfall processes in East Asia using water vapor isotopes. Key Points: δ18Ov values present four patterns under the influence of different weather systems during heavy rainfall eventsMoisture from adjacent oceans and terrestrial environment contribute greatly to the heavy rainfall events in eastern ChinaFluctuations of isotopic values before and after the intermittent period indicate the alteration of nearby oceanic moisture transport [ABSTRACT FROM AUTHOR]

Tropical disturbances frequently occur over the South China Sea and the western Pacific from May to October. Less than half of them can intensify into tropical cyclones, with the majority remaining nondeveloping. This study reveals that nondeveloping low‐level tropical disturbances within the easterly wind belt can also cause heavy rainfall over the northern South China Sea (NSCS, 110°E–120°E, 15°N–20°N) in autumn. Based on a heavy rainfall event in September 2021, physical mechanisms of intensified tropical disturbance‐induced rainfall over the NSCS are investigated. The tropical disturbance at 850 hPa initially originated within easterly winds south of the western Pacific subtropical high and was guided into the NSCS by these easterlies. Meanwhile, the South Asian high disrupted the long‐lasting cyclone‐anticyclone pairs on its southeast side, inducing divergence at 200 hPa, which enhanced the tropical disturbance. Specifically, the upper‐level divergence superimposed on the tropical disturbance intensified ascending motion and low‐level convergence. Above the tropical disturbance, convergence below 400 hPa, combined with vertical and horizontal advection above 500 hPa, together reinforced the vortex structure of the disturbance, facilitating water vapor accumulation. Further results show that cold rain processes above the freezing level were active and significantly contributed to the precipitation. This study provides new insights into heavy rainfall over the NSCS, showing that in the absence of the Intertropical Convergence Zone and cold air, upper‐level divergence promotes the vertical development of the tropical disturbance. The enhanced ascending motion and the increased midupper level moisture intensify cold rain processes and precipitation. Plain Language Summary: The South China Sea and the western Pacific are regions where tropical disturbances are prone to occur. This study reveals that low‐level tropical disturbances within the easterly wind belt, which fail to develop into tropical cyclones, can also cause heavy rainfall over the northern South China Sea (NSCS, 110°E–120°E, 15°N–20°N) in autumn. Analysis of a typical event in September 2021 reveals that the tropical disturbance at 850 hPa initially originated within the easterly winds south of the western Pacific subtropical high and was guided into the NSCS by intensified easterly winds. The precipitation induced by the tropical disturbance was weak initially, but it intensified after the disturbance entered the NSCS. This can be explained by that the South Asian high extended eastward and disrupted the long‐lasting cyclone‐anticyclone pairs at its southeast side, resulting in horizontal wind speed shear. Accordingly, upper‐level divergence formed between strong and weak horizontal wind speeds. The upper‐level divergence superimposed on the low‐level tropical disturbance facilitated ascending motion and convergence, triggering the heavy rainfall over the NSCS. Moreover, the intensified ascending motion and the increased moisture favored the active cold rain processes above the freezing level, making a crucial contribution to the precipitation. Key Points: Low‐level tropical disturbances within the easterly wind belt may cause heavy rainfall over the northern South China SeaThe tropical disturbance and the associated ascending motion tend to be enhanced by the upper‐level divergenceDeeper convection during tropical disturbance supports cold rain processes contributing to the heavy rainfall [ABSTRACT FROM AUTHOR]

Nutrient enrichment impacts grassland plant diversity such as species richness, functional trait composition and diversity, but whether and how these changes affect ecosystem stability in the face of increasing climate extremes remains largely unknown.We quantified the direct and diversity‐mediated effects of nutrient addition (by nitrogen, phosphorus, and potassium) on the stability of above‐ground biomass production in 10 long‐term grassland experimental sites. We measured five facets of stability as the temporal invariability, resistance during and recovery after extreme dry and wet growing seasons.Leaf traits (leaf carbon, nitrogen, phosphorus, potassium, and specific leaf area) were measured under ambient and nutrient addition conditions in the field and were used to construct the leaf economic spectrum (LES). We calculated functional trait composition and diversity of LES and of single leaf traits. We quantified the contribution of intraspecific trait shifts and species replacement to change in functional trait composition as responses to nutrient addition and its implications for ecosystem stability.Nutrient addition decreased functional trait diversity and drove grassland communities to the faster end of the LES primarily through intraspecific trait shifts, suggesting that intraspecific trait shifts should be included for accurately predicting ecosystem stability. Moreover, the change in functional trait diversity of the LES in turn influenced different facets of stability. That said, these diversity‐mediated effects were overall weak and/or overwhelmed by the direct effects of nutrient addition on stability. As a result, nutrient addition did not strongly impact any of the stability facets. These results were generally consistent using individual leaf traits but the dominant pathways differed. Importantly, major influencing pathways differed using average trait values extracted from global trait databases (e.g. TRY).Synthesis. Investigating changes in multiple facets of plant diversity and their impacts on multidimensional stability under global changes such as nutrient enrichment can improve our understanding of the processes and mechanisms maintaining ecosystem stability. [ABSTRACT FROM AUTHOR]

AbstractVarious natural phenomena exhibit spatial extremal dependence at short spatial distances. However, existing models proposed in the spatial extremes literature often assume that extremal dependence persists across the entire domain. This is a strong limitation when modeling extremes over large geographical domains, and yet it has been mostly overlooked in the literature. We here develop a more realistic Bayesian framework based on a novel Gaussian scale mixture model, with the Gaussian process component defined by a stochastic partial differential equation yielding a sparse precision matrix, and the random scale component modeled as a low-rank Pareto-tailed or Weibull-tailed spatial process determined by compactly-supported basis functions. We show that our proposed model is approximately tail-stationary and that it can capture a wide range of extremal dependence structures. Its inherently sparse structure allows fast Bayesian computations in high spatial dimensions based on a customized Markov chain Monte Carlo algorithm prioritizing calibration in the tail. We fit our model to analyze heavy monsoon rainfall data in Bangladesh. Our study shows that our model outperforms natural competitors and that it fits precipitation extremes well. We finally use the fitted model to draw inference on long-term return levels for marginal precipitation and spatial aggregates. [ABSTRACT FROM AUTHOR]

[Objective] The aims of this study are to explore the erosion characteristics of buckwheat fields on the Loess Plateau under heavy rain conditions, to try to analyze the potential influencing factors, and to provide a reference for the management of slope farmland on the Loess Plateau. [Methods] The rainstorm event of 10 th July 2022 in Dingbian, Shaanxi Province were taken as an example. The features of gully erosion on buckwheat land were analyzed based on a combination of remote sensing and field measurements, and the influences on gully erosion on buckwheat land were investigated. [Results] (1) The gully heads within buckwheat farmland affected by severe rainfall tended to form where they intersected with other land types. (2) The average width and depth of rill erosion varied between 5.2 to 29.5 cm and 2 to 19.6 cm, respectively. The ratio of width to depth and the gully density ranged from 0.88 to 3.782 and 0.028 to 1.56 m/m², respectively. The erosion intensity of rill erosion was at a maximum of 20 294.66 t/km². (3) The ephemeral gully had an average width and depth ranging from 37.3 to 173 cm and 8 to 30.7 cm, respectively. The ratio of width to depth and gully densities were 2.161~18.750, and 0.003~0.142 m/m², respectively. Additionally, the maximum intensity of ephemeral gully erosion was 31 629.83 t/km². (4) The gully erosion in buckwheat fields was affected by the slope, length of slope, upstream catchment area, and the measures taken by neighbouring plots. [Conclusion] Compared with other land types such as grasslands and mulched cornfields, gully erosion of the buckwheat slope cropland under heavy rainfall conditions is more severe, and reaches to the intensity of intense erosion. [ABSTRACT FROM AUTHOR]

Based on the daily precipitation data of 2, 424 stations and conventional weather chart data in mainland China in 2021, a statistical analysis of the main heavy rain weather processes from April to October of that year was conducted. The main influencing systems and precipitation situations were outlined, and a comparative analysis of the number of heavy rain days and major heavy rain events from 2008 to 2021 from April to October was performed. The results show that from April to October 2021, China experienced a total of 199 heavy rain days and 32 major heavy rain events. The number of heavy rain days was 10 days more than the average for the previous 13 years (2008-2020), while the number of major heavy rain events remained the same as the average for the previous 13 years. Among them, there were 7 occurrences in July, 6 in May and August each, 5 in June, 4 in September, and 3 in October, with 1 occurrence in April. Among the 32 major heavy rain events, 5 were caused by the landing or influence of tropical cyclones. The northern heavy rain from July 18th to 22nd, including the "7.20" extreme heavy rain in Zhengzhou, was the most widely affected and economically damaging major heavy rain event, with Zhengzhou in Henan Province recording the country's largest daily precipitation of 552.5 mm on July 20th of that year. The maximum accumulated rainfall for a single event in the year reached 820 mm, also occurring in Zhengzhou, Henan Province (July 18th to 22nd) and was caused by the joint influence of a trough, shear line, and warm and humid airflow.

Intense rainfall events frequently occur in Brazil, often leading to rapid flooding. Despite their recurrence, there is a notable lack of sub-daily studies in the country. This research aims to assess patterns related to the structure and microphysics of clouds driving intense rainfall in Brazil, resulting in high accumulation within 1 h. Employing a 40 mm/h threshold and validation criteria, 83 events were selected for study, observed by both single and dual-polarization radars. Contoured Frequency by Altitude Diagrams (CFADs) of reflectivity, Vertical Integrated Liquid (VIL), and Vertical Integrated Ice (VII) are employed to scrutinize the vertical cloud characteristics in each region. To address limitations arising from the absence of polarimetric coverage in some events, one case study focusing on polarimetric variables is included. The results reveal that the generating system (synoptic or mesoscale) of intense rain events significantly influences the rainfall pattern, mainly in the South, Southeast, and Midwest regions. Regional CFADs unveil primary convective columns with 40–50 dBZ reflectivity, extending to approximately 6 km. The microphysical analysis highlights the rapid structural intensification, challenging the event predictability and the issuance of timely, specific warnings.

In engineering practice, slope stability is commonly assessed using a two-dimensional (2D) analysis under the assumption of plane strain conditions. However, when dealing with the complex surface geometries of three-dimensional (3D) slopes, especially under short-term heavy rainfall conditions, relying solely on a 2D cross-sectional analysis may not always yield conservative results compared to 3D slope stability assessments. To investigate the applicability of using 2D cross-sections to represent 3D slopes, this study examines the influence of surface geometries on 3D slope stability. By varying the degree and frequency of surface undulations along a certain longitudinal length of the slope, as well as different variations in slope gradient, the impacts of these factors on the safety factor of 3D slopes under rainfall conditions are analyzed. The findings indicate that for 3D slopes with significant surface undulations and high-frequency variations, the safety factor is generally lower compared to that obtained from the 2D cross-sectional analysis. Furthermore, the variation in slope gradient has a more pronounced effect on the safety factor of 3D slopes compared to surface undulations, particularly when the slope gradients are larger than 50°. Therefore, the influence of spatial dimensions on the stability of slopes can be significant when dealing with complex surface geometries of 3D large-scale slopes. It is highly recommended to conduct both 3D and 2D analyses to ensure the accuracy of the slope stability analysis.

Purposes Origin software was adopted to study the mechanism and final effects of rainwater erosion prevention of Earthen Sites with bare soil and herbs in Western Wall of Jinyang Ancient City. Methods The data analysis method of field artificial simulation rainfall experiment through the software of Origin was used to compare the effects of the underlying surface layer on the runoff and sediment producing processes on the slope surface at different times. Findings Pre-runoff interception Q0 of Fresh Herbs was negatively correlated with runoff starting time T0. And Q0 was in descending order of Dry Herbs, Fresh Herbs, and Bare Soil. Sediment producing coefficient Csy and sediment producing intensity Isy of Fresh Herbs were positively correlated with rainfall intensity Irf. Runoff coefficients Cro and Csy were in descending order of Bare Soil, Dry Herbs, and Fresh Herbs. By forming a mud surface, exposed earthen sites were less affected by rainwater infiltration, making them suitable for arid climate zones. By strengthening anti-erosion, herbal earthen sites reduced soil surface erosion, making them suitable for semi-arid and semi-humid climate areas. Conclusions Origin analysis confirms that herbal plants have a significant effect on improving the anti-erosion of earthen sites. The phenomenon of herbs covering is beneficial to the protection of local earthen sites in Shanxi. However, when extreme sustained heavy rainfall occurs between September and October, further research is needed to determine whether herbal plants are suitable or not for covering earthen sites.

In engineering practice, slope stability is commonly assessed using a two-dimensional (2D) analysis under the assumption of plane strain conditions. However, when dealing with the complex surface geometries of three-dimensional (3D) slopes, especially under short-term heavy rainfall conditions, relying solely on a 2D cross-sectional analysis may not always yield conservative results compared to 3D slope stability assessments. To investigate the applicability of using 2D cross-sections to represent 3D slopes, this study examines the influence of surface geometries on 3D slope stability. By varying the degree and frequency of surface undulations along a certain longitudinal length of the slope, as well as different variations in slope gradient, the impacts of these factors on the safety factor of 3D slopes under rainfall conditions are analyzed. The findings indicate that for 3D slopes with significant surface undulations and high-frequency variations, the safety factor is generally lower compared to that obtained from the 2D cross-sectional analysis. Furthermore, the variation in slope gradient has a more pronounced effect on the safety factor of 3D slopes compared to surface undulations, particularly when the slope gradients are larger than 50°. Therefore, the influence of spatial dimensions on the stability of slopes can be significant when dealing with complex surface geometries of 3D large-scale slopes. It is highly recommended to conduct both 3D and 2D analyses to ensure the accuracy of the slope stability analysis. [ABSTRACT FROM AUTHOR]

Intense rainfall events frequently occur in Brazil, often leading to rapid flooding. Despite their recurrence, there is a notable lack of sub-daily studies in the country. This research aims to assess patterns related to the structure and microphysics of clouds driving intense rainfall in Brazil, resulting in high accumulation within 1 h. Employing a 40 mm/h threshold and validation criteria, 83 events were selected for study, observed by both single and dual-polarization radars. Contoured Frequency by Altitude Diagrams (CFADs) of reflectivity, Vertical Integrated Liquid (VIL), and Vertical Integrated Ice (VII) are employed to scrutinize the vertical cloud characteristics in each region. To address limitations arising from the absence of polarimetric coverage in some events, one case study focusing on polarimetric variables is included. The results reveal that the generating system (synoptic or mesoscale) of intense rain events significantly influences the rainfall pattern, mainly in the South, Southeast, and Midwest regions. Regional CFADs unveil primary convective columns with 40–50 dBZ reflectivity, extending to approximately 6 km. The microphysical analysis highlights the rapid structural intensification, challenging the event predictability and the issuance of timely, specific warnings. [ABSTRACT FROM AUTHOR]

An extra-large landslide occurred on June 19, 2021, on the footwall slope of the Nanfen Open-pit Iron Mine in Liaoning Province, China, with a volume of approximately 1.2×107 m3. To elucidate the causative factors, development process, and destructive mechanisms of this catastrophic landslide, comprehensive field tests, investigations, and laboratory experiments were conducted. Initially, the heavily weathered rock mass of the slope was intersected by faults and joint fissures, facilitating rainwater infiltration. Moreover, the landslide contained a substantial clay mineral with highly developed micro-cracks and micro-pores, exhibiting strong water-absorption properties. As moisture content increased, the rock mass underwent softening, resulting in reduced strength. Ultimately, continuous heavy rainfall infiltration amplified the slope's weight, diminishing the weak structural plane's strength, leading to fracture propagation, slip plane penetration, and extensive tensile-shear and uplift failure of the slope. The study highlights poor geological conditions as the decisive factor for this landslide, with continuous heavy rainfall as the triggering factor. Presently, adverse environmental factors persistently affect the landslide, and deformation and failure continue to escalate. Hence, it is imperative to urgently implement integrated measures encompassing slope reinforcement, monitoring, and early-warning to realtime monitor the landslide's deformation and deep mechanical evolution trends. [ABSTRACT FROM AUTHOR]

Terrace erosion has become increasingly pronounced due to the rising incidence of heavy rainfalls resulting from global climate change; however, the processes and mechanisms governing erosion of loess terraces during such events remain poorly understood. A field investigation was performed following a heavy rainfall event in the Tangjiahe Basin to examine the soil erosion characteristics of loess terraces subjected to heavy rainfall events. The results show that various types of erosion occurred on the terraced fields, including rill, gully, and scour hole in water erosion, and sink hole, collapse, and shallow landslide in gravity erosion. Rill erosion and shallow landslide erosion exhibited the highest frequency of occurrence on the new and old terraces, respectively. The erosion moduli of the gully, scour hole, and sink hole on the new terraces were 171.0%, 119.5%, and 308.7% greater than those on the old terraces, respectively. In contrast, lower moduli of collapse and landslide were observed on the new terraces in comparison to the old terraces, reflecting reductions of 34.2% and 23.4%, respectively. Furthermore, the modulus of water erosion (32,102 t/km2) was 4.5 times that of gravity erosion on the new terraces. Conversely, on the old terrace, the modulus of gravity erosion (8804.1 t/km2) exceeded that of water erosion by 14.5%. Gully erosion and collapse dominated the erosion processes, contributing 67.8% and 9.4% to soil erosion on the new terraces and 38.7% and 34.0%, respectively, on the old terraces. In the study area, the new terraces experienced significantly greater erosion (39,252 t/km2) compared to the old terraces (16,491 t/km2). Plastic film mulching, loose and bare ridges and walls, inclined terrace platforms, and high terrace walls, as well as the developing flow paths, might be the key factors promoting the severe erosion of the terraces during heavy rainfall. Improvements in terrace design, construction technologies, temporary protective measures, agricultural techniques, and management strategies could enhance the prevention of soil erosion on terraces during heavy rainfall events. [ABSTRACT FROM AUTHOR]

This paper presents the results of the recent development of the all-sky radiance assimilation system in the Korean Integrated Model (KIM). In the cycled analysis and forecast experiments, the increased coverage of radiance data in cloudy regions improved the quality of initial fields for mass variables, temperature and humidity. The experimental period covered the record-breaking heavy rainfall event on August 9, 2022. We examined the simulation accuracy of the western North Pacific subtropical high (WNPSH) in both clear- and all-sky experiments. In the clear-sky experiment, northward propagation of the WNPSH was restricted. A humid bias exists with clear-sky radiance assimilation over the WNPSH region. Since humid air is lighter than dry air, in this situation, the geopotential height (GPH) should be lower to achieve the same pressure, and a low-pressure bias occurs. All-sky radiance assimilation dries the moisture field, which helps elevate the GPH over the WNPSH region. The expansion of the WNPSH yielded a steeper confrontation in the air between the land and ocean around the southeastern sea of the Korean Peninsula to predict the strength of rainfall events more accurately. A more accurate simulation of the jet stream outlet was also demonstrated in an all-sky experiment. This study shows that the all-sky radiance assimilation can help to more accurately predict extreme rainfall events via proper simulations of large-scale fields. [ABSTRACT FROM AUTHOR]

South China stands out as one of the regions experiencing the longest flood season and the highest frequency of floods in China. Understanding the characteristics of heavy precipitation during the flood season and its potential mechanisms is crucial for predicting and preventing flood disasters in South China. In this study, we classify regional heavy precipitation during the pre-flood season in South China into frontal heavy rainfall (FR) and warm-sector heavy rainfall (WR). FR is mainly controlled by the southwest monsoon and the westerly jet in the northwest of the West Pacific Subtropical High (WPSH). The westerly wind brings abundant water vapor to the front, creating an unstable environment conductive to heavy rainfall events. In instances of WR, precipitation occurs in warmer regions due to the northward movement of warm and humid air from the western side of the WPSH, coupled with the westerly jet transporting warm and humid air to the mainland. These atmosphere processes contribute to ascent, condensation, and the subsequent formation of heavy rainfall. Investigating the extended-range period predictability of the National Centers for Environmental Prediction (NCEP) sub-seasonal to seasonal (S2S) forecast system for these two types of heavy rainfall reveals a diminishing predictability for FR and WR as forecast lead time increases. Notably, NCEP S2S demonstrates superior prediction skill for FR compared to that for WR. The diminished prediction skill for WR within NCEP S2S primarily stems from model inadequacies related to forecasting atmospheric circulation and water vapor transport anomalies associated with WR. When forecasting WR, the easterly wind anomaly has influence the upper troposphere since the model's prediction 10 days in advance. Simultaneously, the model faces challenges in accurately predicting the characteristics of the WPSH and water vapor transport anomalies originating from the Bay of Bengal. Moreover, the model is unable to predict the influence of the Eurasian (EU) wave train on WR beyond the lead time of 20 days. These issues can be ascribed (attributed) to the absence of a distinct weather-scale boundary (front) for WR in the model, rendering the forecast of WR inherently more challenging compared to that of FR. [ABSTRACT FROM AUTHOR]

Disasters caused by heavy rainfall associated with quasi-stationary line-shaped mesoscale convective systems (MCSs) frequently occur in Japan. Thus, highly accurate quantitative precipitation forecast (QPF) information that contributes to decision-making by municipalities to issue evacuation orders is necessary. To this end, we developed a blending forecasting system (BFS) for predicting heavy rainfall associated with MCSs. The BFS blends 1-h observed rainfall and forecasts of extrapolation-based nowcasting (EXT) in the first hour and numerical weather prediction (NWP) in the second hour, predicting 3-h accumulated rainfall (P3h) and its return period (RP) of up to 2 h ahead with a higher horizontal resolution (1 km) and higher-frequency updates (every 10 min) compared to the current operational systems. A blending technique with a spatial maximum filter for tolerating forecast displacement errors (BLEDE) was applied to the predicted rainfall of EXT and NWP. To improve the accuracy of the NWP, vertical profiles of water vapor obtained with two water vapor lidars (WVLs) were assimilated into the NWP. This combination predicted rare heavy rainfall with an RP of more than 10 years in the same city where flooding occurred for a heavy rainfall event associated with quasi-stationary line-shaped MCSs in southern Kyushu on 10 July 2021. The BFS yielded such forecast information 40 min earlier than the existing warning information, indicating the potential for providing a longer lead time for evacuation. The improvement in forecast accuracy was due to both BLEDE and WVL data assimilation (WVL-DA); however, the contribution of BLEDE was more than five times that of WVL-DA in terms of predicting the P3h for the threshold of 80 mm. Additionally, the sensitivity of the predicted rainfall to the background error covariance matrix in WVL-DA is also discussed. [ABSTRACT FROM AUTHOR]

To study the formation mechanism of rainfall‐induced soil erosion, collapse and landslides in the Loess Plateau based on the unsaturated soil seepage theory and the effective stress principle, the failure process of collapse with cracks under heavy and long‐term rainfall was investigated using the finite element method. The results showed that under the action of heavy rain, surface run‐off quickly gathered in cracks to form a dominant flow, resulting in a rapid increase in the water level and hydrostatic pressure in the cracks. The strength of the soil at the tip of the crack decreased rapidly under the softening effect of the water, and tensile failure occurred. The crack accelerated downward to the foot of the slope, causing the steep slope to collapse. Long‐term rainfall acts directly on the soil near the crack, resulting in faster saturation than the soil inside the slope body. When the rainfall time exceeded a certain value, the soil near the crack reached a saturated state, and the soil strength was minimized. Simultaneously, the seepage force generated when rainwater inside the collapsed body seeps from its outer edge increases the overturning moment of the collapsed body. Under the continuous action of rainfall, the cracks gradually extended to the foot of the slope, causing the collapsed body to fail. These research results provide a theoretical basis for the prevention and control of land degradation and collapse disasters on the Loess Plateau. [ABSTRACT FROM AUTHOR]

To investigate the influence of tree roots on the triggering mechanism of shallow landslides, this study focused on a typical vegetation-covered cluster landslide in the Wuping area of China. A tree root profile investigation and a double-ring infiltration test were conducted. The undisturbed soil samples were collected for laboratory tests to measure the influence of tree vegetation on soil physical and hydraulic properties. The root reinforcement effect is limited by the depth of root distribution, with over 90% of the roots situated above the slip surface. The presence of roots increases the resistance of the soil to disintegration. The soil disintegration in the 0–80 cm layer was less than 25% after 24 h of water immersion and the soil undergoes complete disintegration at a depth of 180–200 cm within 120 s. Tree roots facilitate the infiltration of soil, and Ks at 0 m was 11.21 times than that at 2 m, and the interface between soils with roots and soils without roots may become a sliding surface. Under extreme rainfall conditions, the root system promotes water infiltration, accelerates the softening and disintegration of the soil on the sliding surface, which adversely affects the stability of landslides.

In this article, we document the use of hail cannons in Mexico to dispel or suppress heavy rain episodes, a common practice among farmers, without scientific evidence to support its effectiveness. This study uses two rain databases: one compiled from the Global Precipitation Measurement (GPM) mission and the other generated with the implementation of the Weather Research and Forecasting (WRF) model. The aim is to explore the association between heavy rain episodes and hail cannon locations. The analysis includes two geographic features: a pair of coordinates and a 3 km radius area of influence around each hail cannon. This dimension is based on the size and distribution of the heavy rainfall events. This study analyzes four years of half-hourly rain data using the Python ecosystem environment with machine learning libraries. The results show no relationship between the operation of hail cannons and the dissipation or attenuation of heavy rainfall events. However, this study highlights that the significant differences between the GPM and WRF databases in registering heavy rain events may be attributable to their own uncertainty. Despite the unavailability of ground-based observations, the inefficiency of hail cannons in affecting the occurrence of heavy rain events is evident. Overall, this study provides scientific evidence that hail cannons are inefficient in preventing the occurrence of heavy rain episodes.

Heavy rainfall is an important weather that causes flood disasters, and it is also one of the most important natural disasters in our country. With development of the high-resolution numerical models, numerical weather prediction has been the main method for heavy rainfall forecasting. However, the accuracy of the numerical prediction depends on the completeness of the atmospheric motion equations, the accuracy of the initial state, the reasonability of the physical process, and the robustness of the calculation method. As the atmosphere is a nonlinear chaotic system, the small errors in these aspects will cause significant uncertainty in the forecast results. Therefore, the improvement of the rainstorm numerical prediction is closely related to the development of data assimilation, parameterization of physical processes, and ensemble prediction, especially for the role of parameterization schemes of cloud microphysical processes that produce precipitation in numerical models. In addition, in order to improve and perfect the numerical model, the investigation of the evaluation method of the forecast results can also not be ignored and is a crucial part of the numerical prediction. This review describes the development of several key numerical weather prediction techniques. The four-dimensional ensemble variational assimilation method, the microphysics parameterization scheme, and the stochastic kinetic energy backscatter method of ensemble prediction model perturbation are highlighted. An evaluation method of model results based on kinetic energy spectrum analysis is also proposed. Finally, the future research directions in these aspects are summarized.

In the Hokitika region, on the west coast of the South Island of New Zealand on 18 June 2015, very heavy stratiform precipitation (>200 mm/per day) occurred under north-westerlies with small CAPE (<25 J/kg). Analyses of model simulations and observations showed that this heavy rainfall was due to cold-front lifting enhanced by orographic lifting over the Southern Alps. At 1.5 km grid-length, the model terrain underestimated the average height of the 103 tallest mountains over the South Island by ~800 m. This led to weaker orographic lifting and mountain blocking, and a faster-moving and stronger cold front in the Hokitika region. As a result, large errors in the heavy rainfall prediction occurred. By increasing either the resolved or the sub-grid mountain heights, the simulated rainfall errors were largely reduced through stronger orographic lifting and mountain blocking, and simulation of the cold front movement and strength was improved. All the experiments have the same "flow-over" regime with mountain waves and/or wave breaking ( F m ranges 0.61–1.21). However, the rainfall amount and distribution on the windward side of the mountains varied significantly. Our new findings were that the Southern Alps can have significant indirect effects on heavy rainfall by altering the speed and strength of the cold front, in addition to the well-known direct dynamical effects (i.e., orographic lifting and mountain blocking). A combination of these direct and indirect effects makes the heavy rainfall simulation sensitive to mountain heights even under the same "flow-over" regime. [ABSTRACT FROM AUTHOR]

This study provides a thorough analysis of the landslides that occurred in the city of São Sebastião, on the northern coast of São Paulo state, Brazil, in February 18th–19th, 2023. The meteorological condition during this event was characterized by a cold front crossing over a warmer-than-normal subtropical South Atlantic, off the coast of São Paulo. Combined with the orographic effect of the Serra do Mar Mountain, the front remained stationary over the northern coastal areas of the state of São Paulo, causing an extreme and historic heavy precipitation event. An unprecedented volume of rain, amounting to 683 mm in less than 15 h, triggered landslides that generated 65 casualties and damages. Although alerts were clearly issued in advance, response among the communities was minimal, indicating the ineffectiveness of current early warning system in place. This calls for improved public policies, communication and the possible adoption of multi-hazard early warning systems to reduce risk in vulnerable areas. [ABSTRACT FROM AUTHOR]

Powerlines are strategic infrastructures for the Italian electro-energetic network, and natural threats represent a potential risk that may influence their operativity and functionality. Geo-hydrological hazards triggered by heavy rainfall, such as shallow landslides, have historically affected electrical infrastructure networks, causing pylon failures and extensive blackouts. In this work, an application of the reworked version of the model proposed by Borga et al. and Tarolli et al. for rainfall-induced shallow landslide hazard assessment is presented. The revised model is called SLEM (Shallow Landslide Express Model) and is designed to merge in a closed-from equation the infinite slope stability with a simplified hydrogeological model. SLEM was written in Python language to automatise the parameter calculations, and a new strategy for evaluating the Dynamic Contributing Area (DCA) and its dependence on the initial soil moisture condition was included. The model was tested for the case study basin of Trebbia River, in the Emilia-Romagna region (Italy) which in the recent past experienced severe episodes of geo-hydrological hazards. The critical rainfall ratio (rcrit) able to trigger slope instability prediction was validated against the available local rainfall threshold curves, showing good performance skills. The rainfall return time (TR) was calculated from rcrit identifying the most hazardous area across the Trebbia basin with respect to the position of powerlines. TR was interpreted as an index of the magnitude of the geo-hydrological events considering the hypothesis of iso-frequency with precipitation. Thanks to its fast computing, the critical rainfall conditions, the temporal recurrence and the location of the most vulnerable powerlines are identified by the model. SLEM is designed to carry out risk analysis useful for defining infrastructure resilience plans and for implementing mitigation strategies against geo-hazards. [ABSTRACT FROM AUTHOR]

In numerical weather prediction (NWP), the parameterization of orographic drag plays an important role in representing subgrid orographic effects. The subgrid orographic parameters are the key input to the parameterization of orographic drag. Currently, the subgrid orographic parameters in most NWP models were produced based on elevation datasets generated many years ago, with a coarse resolution and low quality. In this paper, using the latest high-quality elevation data and considering the applicable scale range of the subgrid orographic parameters, we construct the orographic parameters, including the subgrid orographic standard deviation, anisotropy, orientation, and slope, that are required as input to the orographic gravity wave drag (OGWD) parameterization. Finally, we introduce the newly constructed orographic parameters into the Yin-He Global Spectral Model (YHGSM), optimize the description of the orographic effect in the model, and improve the simulation of two typical heavy rainfall events in Beijing and Henan. [ABSTRACT FROM AUTHOR]

In this article, we document the use of hail cannons in Mexico to dispel or suppress heavy rain episodes, a common practice among farmers, without scientific evidence to support its effectiveness. This study uses two rain databases: one compiled from the Global Precipitation Measurement (GPM) mission and the other generated with the implementation of the Weather Research and Forecasting (WRF) model. The aim is to explore the association between heavy rain episodes and hail cannon locations. The analysis includes two geographic features: a pair of coordinates and a 3 km radius area of influence around each hail cannon. This dimension is based on the size and distribution of the heavy rainfall events. This study analyzes four years of half-hourly rain data using the Python ecosystem environment with machine learning libraries. The results show no relationship between the operation of hail cannons and the dissipation or attenuation of heavy rainfall events. However, this study highlights that the significant differences between the GPM and WRF databases in registering heavy rain events may be attributable to their own uncertainty. Despite the unavailability of ground-based observations, the inefficiency of hail cannons in affecting the occurrence of heavy rain events is evident. Overall, this study provides scientific evidence that hail cannons are inefficient in preventing the occurrence of heavy rain episodes. [ABSTRACT FROM AUTHOR]

The advancement of Numerical Weather Prediction (NWP) is pivotal for enhancing high-impact weather forecasting and warning systems. However, due to the high spatial and temporal inhomogeneity, the moisture field is difficult to describe by initial conditions in NWP models, which is the essential thermodynamic variable in the simulation of various physical processes. Data Assimilation techniques are central to addressing these challenges, integrating observational data with background fields to refine initial conditions and improve forecasting accuracy. This study evaluates the effectiveness of integrating observations from the Fengyun-4A (FY-4A) Advanced Geosynchronous Radiation Imager (AGRI) and ground-based microwave radiometer (MWR) in forecasts and mechanism analysis of a heavy rainfall event in the Kaifeng region of central China. Our findings reveal that jointly assimilating AGRI radiance and MWR data significantly enhances the model's humidity profile accuracy across all atmospheric layers, resulting in improved heavy rainfall predictions. Analysis of the moisture sources indicates that the storm's water vapor predominantly originates from westward air movement ahead of a high-altitude trough, with sustained channeling towards the rainfall zone, ensuring a continuous supply of moisture. The storm's development is further facilitated by a series of atmospheric processes, including the interplay of high and low-level vorticity and divergence, vertical updrafts, the formation of a low-level jet, and the generation of unstable atmospheric energy. Additionally, this study examines the influence of Tai-hang Mountain's terrain on precipitation patterns in the Kaifeng area. Our experiments, comparing a control setup (CTL) with varied terrain heights, demonstrate that reducing terrain height by 50–60% significantly decreases precipitation coverage and intensity. In contrast, increasing terrain height enhances precipitation, although this effect plateaus when the elevation increase exceeds 100%, closely mirroring the precipitation changes observed with a 75% terrain height increment. [ABSTRACT FROM AUTHOR]

Meteorological processes are investigated during the development of deep convective clouds over the Yellow Sea inside a quasi‐stationary rainy front in the East Asian region. WRF‐Chem simulations were conducted to assess the effects of aqueous‐phase chemistry on the concentrations of PM2.5 and hydrometers in deep convective clouds and the associated precipitation. A reduction in the south‐north air temperature gradient induced an inactive quasi‐stationary rainy front with nonlinear zonal clouds during the Changma period in the East Asian region in 2017, causing intensified surface heating due to solar radiation. A mesoscale cyclone was formed near the Shantung Peninsula inside the inactive quasi‐stationary rainy front, extending the eastward tongue of the troughs across the Yellow Sea. Deep convective clouds (CC16 on July 16, CC17 on July 17, and CC18 on July 18) formed in a severe mode on the east side of the mesoscale cyclone over the Yellow Sea at midnight as the warm type, as the warm and humid south‐southwesterly winds present at that time produced convection energy. PM2.5 from eastern China flowed into warm‐type CC16, CC17, and CC18 areas, producing more cloud droplets below 500 hPa via activation. In contrast, the release of additional condensation heat amplifies updrafts within convective clouds during efficient nighttime environmental cooling, thereby enhancing the production of cold‐type ice, reaching altitudes of up to 15 km. The WRF‐Chem PM2.5 outcomes indicate a significant increase in heavy rainfall, exceeding 10 mm hr−1, particularly in the context of the development of cold‐type convective clouds. Plain Language Summary: The regional phenomenon of summer rain, known as Changma in Korea, usually occurs with a quasi‐stationary rainy front that forms between the continental polar air mass over the East Asian region and the maritime tropical air mass over the northwest Pacific. An inactive quasi‐stationary rainy front with nonlinear zonal clouds induced by a reduction in the south‐north air temperature gradient during the Changma period led to the efficient absorption of solar radiation on the surface of the East Asian region. In addition, convective clouds have frequently developed over the Yellow Sea inside the inactive quasi‐stationary rainy front, resulting in extreme events with large amounts of short‐term precipitation in inland Korea. We found that aqueous‐phase chemistry in convective clouds led to the production of PM2.5 and nucleated cloud droplets, enhancing precipitation on 16–18 July 2017. While warm‐type convective clouds developed due to warm and humid south‐southwesterly flows over the Yellow Sea, WRF‐Chem‐simulated PM2.5 promoted cold‐type ice production to a top convection height of 15 km. The entrainment of near‐surface PM2.5 aerosols in the south‐southwesterly flows from eastern China and the secondary activations over the boundary layer clouds enhanced heavy rainfall to more than 10 mm hr−1 in cold‐type convective clouds. Key Points: A reduction in the air temperature gradient induced an inactive rainy front, forming a mesoscale cyclone over the Yellow SeaPM2.5 aerosols in eastern China flowed out to the Yellow Sea, wherein the PM2.5 inflows contributed to the development of cold‐type cloudsCold‐type clouds promoted heavy rainfall exceeding 10 mm hr−1 over the Yellow Sea and Korea [ABSTRACT FROM AUTHOR]

Tunnel invert damage will lead to track misalignment and consequently seriously affect the operation safety of the railway line. In this paper, the rainfall intensity, geological conditions, and damage manifestations were studied by reviewing cases with tunnel invert damage induced by heavy rainfall (HR-TID) in China over the last two decades. Based on the Malazhai Tunnel of the Shanghai-Kunming Railway, the effects of rainfall levels and drainage system blockage ratio on the water pressure outside the tunnel and its structure deformation were investigated through scaled-down modeling tests. The evolution mechanism of HR-TID was demonstrated based on the results of field studies and model tests, which in turn bring out sound proposals of treatment measures for HR-TID. It is manifest that heavy rainfall events, catchment topography, highly permeable ground, and the development of karst fissures are key factors leading to tunnel invert damage. With the increase of rainfall and blockage ratio of the drainage system, the water pressure in the proximity of the tunnel bottom increases rapidly, leading to the tunnel invert uplift and making a worse working condition at the tunnel invert. To ensure operation safety, emergency treatment should be put into effect as soon as possible to resume tunnel drainage operation, following the long-term treatment of blocking the infiltration channels and paths. The effectiveness of treatment for HR-TID presented in the case study can provide as a promising reference for similar tunnel projects. [ABSTRACT FROM AUTHOR]

Based on hourly ERA5 reanalysis and station rainfall data of China, this study investigated the mesoscale anomalous atmospheric circulation linked with heavy rainfall events around Yaan China. Yaan located in steep terrain on the eastern foot of Tibetan Plateau and is in the trumpet corner region of western Sichuan Basin of China. Yaan areas serve as a regional heavy rainfall center. Analysis revealed that the principal atmospheric circulation features, which underpin heavy rainfall, is probably a mesoscale (within 500 km) anomalous circulation system characterized by anomalous upper tropospheric warming (around 300–500 hPa) and lower stratospheric cooling (around 100 hPa) above Yaan, which against large-scale upper tropospheric backgrounds either warm or cold over East China. The anomalous temperature pattern corresponds to a positive (negative) geopotential height anomaly and mesoscale divergence (convergence) at 150–200 hPa (800–925 Pa). The anomalous low-level easterly winds blowing towards the steep terrain, together with the upper-level divergence, favor the occurrence of heavy rainfall around Yaan. The formation of the mesoscale upper-level warm anomaly over Yaan under a large-scale cold background could be contributed by the interaction between the stratosphere and troposphere, the transport of warm air mass from the northern Tibetan Plateau in the upper troposphere and also the match of middle-lower tropospheric warm anomalies jointly. The findings of this study highlight the importance of the influence of upper-tropospheric mesoscale circulations to heavy rainfall. [ABSTRACT FROM AUTHOR]

Internal erosion is capable of leading to substantial soil losses and piping erosion in prolonged rainfall scenarios and the research about it poses a significant challenge. The current landscape lacks comprehensive insights into evaluating internal erosion at both macro- and micro-scales. To address this gap and quantitatively assess soil erosion, we define the erosion factor as the rates of change of various parameters, encompassing microstructure, soil resistivity, and slope erosion morphology characteristics. An indoor rainfall erosion experiment was meticulously crafted, integrating computed tomography (CT) and electrical measurements. Results unveil the nonlinear dynamics of internal particle losses and fracture generations concerning rainfall intensity. Erosion factors, defined by micro-parameters like fractal dimension and probability entropy, exhibit an exponential correlation with resistivity change rates. Furthermore, a three-dimensional (3D) model test was conducted, employing 3D scanning and electrical measurement. Digital elevation models (DEMs) illustrate the formation of splash pits across the slope and the expansion of erosion rills, particularly in low-lying areas. Two resistivity profiles exhibit similar increasing trends attributed to internal erosion. Classifying erosion states based on erosion factors of macro-deformation parameters and soil resistivity underscores spatiotemporal characteristics, notably downward evolution, maintaining consistency between surface and internal erosion. Subsequently, electrical measurement validated internal erosion induced by infiltration channels in in-situ slopes before and after the rainy season. In conclusion, this study unveils intricate relationships among resistivity, macro- and micro-parameters, highlighting the promising potential of electrical measurements in nuanced internal erosion evaluation. [ABSTRACT FROM AUTHOR]

Heterogeneous rock masses that include rhythmic alternations of marl, shale, marly limestone, sandstone, siltstone, and argillite, such as Flysch, are particularly prone to generating colluvial deposits on gentle slopes, which are often subject to failures triggered by heavy rainfall. Flysch-derived colluvial soils are made up of highly heterogeneous sediments ranging from clayey loam to rock fragments, and they have been studied more rarely than homogeneous soils. In this work, we present a geotechnical and hydraulic characterisation performed both in situ and in the laboratory on flysch-derived colluvial soils that were involved in a channelised landslide in the pre-alpine area of the Friuli Venezia Giulia region (NE Italy). The investigated soils were characterised by the average values of the grain size composition of about 25% gravel, 20% sand, 30% silt, and 25% clay. The loamy matrix presented low-to-medium values of the liquid and plastic limits, as well as of the plasticity index (LL = 40%, PL = 23%, and PI = 17%, respectively). The values of the peak friction angle for natural intact samples were 33° < ϕ'p < 38°, whereas the residual friction angle fell to 23–24° at great depths and high vertical stresses, for a prevailing silty–clayey matrix. Variable head permeability tests were performed both in situ and in the laboratory, showing that the values of the vertical and horizontal permeability were very close and in the range 1 × 10−4–1 × 10−6 m/s. The soil permeability measured in the field was generally higher than the hydraulic conductivity calculated on laboratory samples. The proposed geotechnical and hydrological characterisation of flysch-derived colluvial soils can be of fundamental importance before the use of more thorough analyses/models aimed at forecasting the possible occurrence of slope failures and evaluating the related landslide hazard. The reported geotechnical and hydraulic parameters of flysch-derived colluvial materials can represent a useful reference for rainfall infiltration modelling and slope stability analyses of colluvial covers that are subject to intense and/or prolonged precipitation. However, when facing engineering problems involving colluvial soils, particularly those coming from flysch rock masses, the intrinsic variability in their grain size composition, consistency, and plasticity characteristics is a key feature and attention should be paid to the proper assumption of the corresponding geotechnical and hydraulic parameters. [ABSTRACT FROM AUTHOR]

Volcanic regions have complicated groundwater flow systems because of their geological structures, and the effects of rainfall on their groundwater recharge/discharge are still largely unknown. A field survey and chemical analyses were conducted on springs near an andesitic volcano in Japan to investigate changes in groundwater flow processes associated with heavy rainfall. After heavy rainfall, some springs showed a decrease in tracer values while others at lava or pyroclastic flow termini were stable. This indicates that the rainfall component rapidly discharges or the bedrock groundwater component discharges from deeper subsurface areas depending on the structure, length, and permeability of the volcanic ejecta. Hence, the groundwater mixing process in areas with ejecta can be approximated by the binary mixing model. In contrast, tracer values increased after heavy rainfall in areas near agricultural land, which suggests that nitrate ions were loaded into groundwater. Thus, the changes in various groundwater flow processes in volcanic regions after rainfall can be attributed to not only geological/geographical differences but also the groundwater stored in mountain bodies. [ABSTRACT FROM AUTHOR]

This study analyzed the regional climate variations in heavy rainfall across South China by using the IMERG precipitation data during 2001--2020. The research focused on the spatiotemporal distribution characteristics of heavy rainfall and the diurnal variations of extreme heavy rainfall before, during, and after the onset of the South China Sea summer monsoon. The results showed that: (1) The rainfall center in South China was influenced by diverse weather systems at different times of the year. The ratios of rainfall during the two rainy seasons to the annual precipitation were inversely distributed, and the proportion of heavy rainfall along the coast of Guangdong and Guangxi was significantly higher than those of other regions. Heavy rainfall contributed the most to the overall precipitation in the rainfall center of South China. (2) The coastal areas of Guangdong experienced two peaks of heavy rainfall in June and August, while Hainan Island observed a single peak in October. Other regions of Guangdong and Guangxi exhibited a single peak in June, which was closely related to the onset of the South China Sea summer monsoon. During the onset of the summer monsoon, the strong summer monsoon intensified the heavy rainfall in Zone I (Beibu Gulf), Zone II (area near Yangjiang), and Zone III (Pearl River Delta) along the coastal land areas of Guangdong and Guangxi. In the second rainy season, the summer monsoon continued to contribute to increased heavy rainfall across the entire coastal area and Hainan Island. In early June, Zone III and Zone IV (Shanwei and its eastern region) experienced a high frequency of heavy rainfall, primarily due to warm-sector heavy rainfall induced by the southwest summer monsoon. (3) Hainan Island exhibited the highest occurrence of extreme heavy rainfall in South China, predominantly in the afternoon. Guangdong followed with a lower occurrence, while Guangxi experienced the lowest occurrence. The diurnal variation of extreme heavy rainfall was most pronounced in the morning along the coastal area of Guangdong and Guangxi, especially from early morning to forenoon (5--11 am), which corresponded to the peak period in Zone II and Zone III. Inland areas of Guangdong only exhibited a peak period in the evening during the onset of summer monsoon. [ABSTRACT FROM AUTHOR]

On August 7, 2023, Mangshi City, Dehong Prefecture experienced a local heavy rainstorm, and the geological disaster caused by the heavy rainfall caused casualties and property losses. Based on the real-time observation data of automatic stations, Doppler weather radar detection and meteorological risk warning products, the disaster situation, social impact, forecast and early warning service, causes of heavy precipitation and forecast and early warning inspection were summarized and analyzed. The results show that the heavy rainfall was prominent locally, lasted for a long time and accumulated a large amount of rainfall. There were biases in model products, and it was difficult for forecasters to make subjective corrections in complex terrain. The analysis ideas and focus points of heavy rainfall forecast, the improvement ideas and technical schemes of forecast deviation, and the improvement ideas and suggestions of services were summarized. It provides a reference for the forecast and early warning of severe weather in the future. [ABSTRACT FROM AUTHOR]

The concept of compound hazards refers to the simultaneous occurrence or rapid succession of multiple hazards within a specific area. In this study, we identified compound meteorological hazards based on three types of individual hazards: high temperatures, heavy rainfall, and tropical cyclones (TCs). We computed the number of each type of individual hazards and their compounds at 10 selected stations along the coastline of Vietnam for the period 1980–2018. A temperature hazard (rainfall hazard) is identified if the maximum temperature (rainfall amount) on a given day exceeds the 95th percentile of all daily values recorded over the study period. A location is considered exposed to a TC hazard on a given day if the distance from that location to the TC center is less than 250 km. Subsequently, a compound hazard event is identified if the interval between the ending time of one individual hazard event and the starting time of the following one is less than 10 days. The results indicate that the annual number of compound hazards shows increasing trends at the majority of the stations, mainly due to the increase in temperature hazards. At the seasonal scale, compound hazards typically occur from March to November, primarily associated with temperature hazards in the first half of the year and with TCs and rainfall hazards in the later months. The identification and analysis of compound hazards in this study provide essential information for resilience and adaptation planning in Vietnam. [ABSTRACT FROM AUTHOR]

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The Canadian province of British Columbia (BC) is subjected to large-scale, destructive floods. The most dramatic was a mid-November 2021 event when atmospheric rivers (ARs) linked to high-intensity storms caused heavy rainfall in southwestern BC, triggering catastrophic flooding. This study examines 37 floods from 2000 to 2021 using information from over 250 climatological stations and compares events with the mid-November 2021 flood. The dates of the floods showed a bi-modal pattern: a primary season (spring to early summer, 16 floods) and a secondary season (fall to early winter, 21 floods). Five mechanisms controlled these floods: heavy rainfall, rapid snowmelt, severe ice jam, rain-on-snow, and a mixture of snowmelt and ice jam; the mid-November 2021 flood was mainly driven by heavy rainfall. Of the 37 floods, those affected by either heavy rainfall (18 floods) or rain-on-snow (10 floods) were used to derive a relationship between the average daily precipitation amount over the duration of an event and the associated integrated water vapour transport IVT¯. Flood events showed a strong linear relationship between these variables with R2 ≥0.85, p 90% of the others, although they were not the highest. The mid-November 2021 flood was also one of the four rainfall-related floods that occurred in the secondary season with IVT‾ > 400 kg m−1 s−1. The frequency of flood events over the last five years of the study period has slightly decreased when considering flood events with unknown insured cost. In contrast, insured costs of these events have increased, suggesting that present-day floods are becoming more impactful and may require changes to flood management strategies to reduce costs.

In recent years, line-shaped rainbands (LRBs) have increased in Hokkaido, Japan. LRBs caused several flood disasters historically, thus the weather patterns that cause them need to be investigated. This study aimed to understand statistically the relationship between LRBs and weather patterns during the summer months under climate change conditions. Our study investigates the link between LRBs and weather patterns in Hokkaido during July and August, using historical and climate prediction models. With a 2°/4° global temperature rise, LRB occurrences in this region increase by approximately 1.51/2.07 times. The highest occurrences of LRBs correlate with increased water vapor flux from the south and positive pressure anomalies over the Pacific Ocean. Three main weather patterns contribute significantly to LRBs: (1) a nearby low-pressure system, (2) a strengthening Pacific High frontal pattern, and (3) approaching or landing typhoons in Hokkaido. These patterns double the LRB occurrence probability, a trait observed across past and projected climates (+2K and +4K experiments). These are important insights for future flood risk management. HIGHLIGHTS Integrative technical approach in hydroinformatics proposed for the first time.; The novel framework was introduced for the analysis of massive climate data.; Important new insights into line-shaped rainbands are provided.; Important insights into the effects of climate change are provided.; Significant enhancement in understanding summer meteorological fields contributing to heavy rainfall.;